A variational approach to stable principal component pursuit Conference Proceeding uri icon

Overview

abstract

  • We introduce a new convex formulation for stable principal component pursuit; (SPCP) to decompose noisy signals into low-rank and sparse representations. For; numerical solutions of our SPCP formulation, we first develop a convex; variational framework and then accelerate it with quasi-Newton methods. We; show, via synthetic and real data experiments, that our approach offers; advantages over the classical SPCP formulations in scalability and practical; parameter selection.

publication date

  • June 4, 2014

Full Author List

  • Aravkin A; Becker S; Cevher V; Olsen P